AI Agents in DeFi: Revolutionizing Financial Markets with Intelligent Systems

AI Agents Need Their Own DeFi Layer To Succeed in Financial Markets

AI agents don't just replace human traders by being faster, they are completely different entities with fundamentally different requirements. Credit: Pexels. We are seeing a growing interest in agentic frameworks that can seamlessly integrate web3 applications into AI agent functionalities, marked by the thought leadership of industry figures such as Eliza Labs, the developer behind ai16z. Over one million AI agents are expected to run on blockchain networks by the end of 2025. But as AI agents evolve from simple bots executing pre-programmed tasks to autonomous entities capable of complex decision-making, the limitations of existing decentralized finance (DeFi) systems will become increasingly obvious. DeFi as it stands today was built for general-purpose cryptocurrencies and human traders -- not for the sophisticated, adaptive, and fast-moving world of agentic AI. If we want AI to thrive in financial markets, it needs its own DeFi layer, a system designed specifically for its unique needs. Autonomous DeFi agents We are already witnessing AI agents being able to access DeFi markets, interpret qualitative data, and execute profit-generating strategies without human oversight. Spanning anything from robo-advisors to institutional AI agents performing tasks like risk assessment and portfolio optimization these bots will be able to analyze speeches, decode market sentiment, and adapt their strategies in real-time for things like managing liquidation risks. Essentially, they'll operate like hedge fund managers but faster and more precise, unlike existing DeFi bots that simply analyze quantitative data and react to price changes, The problem lies in DeFi's lack of an intelligence layer. The financial mechanics of DeFi are misaligned with the needs of AI-driven economies. AI agents require fast, reliable, and stable currencies to transact with each other seamlessly. Cryptocurrencies like Ethereum or Bitcoin are too volatile and slow for this purpose. AI agents trying to execute a high-frequency trading strategy cannot be stalled by network congestion. Making Stablecoins Intelligent Intelligent stablecoins could act as a foundation for AI-driven economy, allowing agents to pay for services and settle transactions with stable, AI-native currencies designed for speed and reliability. It would create a financial ecosystem where AI agents can operate autonomously. Referred to as "AI USDs", algorithmic stablecoins can be issued using an AI token as a reserve asset, relying on different stability mechanisms depending on the project's risk profile. When minting AI USDs, one could rely on a mint-and-burn equilibrium mechanism, whereby assets in reserve fully back the outstanding dollar value of the AI USD minted, or stablecoins could be minted by using AI native tokens as collateral. Currently, AI tokens lack long-term utility beyond speculation, even for top-tier projects. By integrating AI tokens into stablecoin issuance, projects can incentivize holding, ensuring continued support for AI development. This approach strengthens DeFi participation, stabilizes token prices, and aligns incentives between AI builders and their communities -- laying the financial groundwork for an AI-native economy. AI Agents Require a Different Approach Critics might argue that building a separate DeFi layer for AI is unnecessary and that existing infrastructure can be adapted to meet these needs. But this misses the point. AI agents don't just replace human traders by being faster; they are completely different entities with fundamentally different requirements. Trying to fit AI into a system designed for humans is like trying to run a Formula 1 car on a dirt road. It might work for a while, but it's not sustainable.

How to utilize AI agents in decentralized finance (DeFi) platforms

Despite their potential, AI agents face challenges such as reliance on high-quality data, regulatory uncertainties and vulnerability to security risks. Imagine a world where trading is no longer limited to human financial knowledge and capacities. In this world, machines don't just execute trades but also adapt and continuously optimize strategies on their own. This isn't the distant future; it's the reality emerging in decentralized finance (DeFi) today, thanks to AI agents. AI agents are self-operating software programs that can make decisions independently, without human interaction. They use machine learning algorithms to refine their processes and adapt continuously. In traditional finance, AI has already transformed trading, risk management and customer service. In DeFi, where trust is built on code, not intermediaries, AI has opened new avenues for autonomy, transparency and effectiveness. This article will explore what AI agents are and how to utilize AI in DeFi platforms. AI agents are like helpful robots that live inside DeFi platforms and manage finances. They're integrated with smart contracts and decentralized applications (DApps), which function like regular apps but instead are run on a blockchain. Some DeFi platforms have AI agents integrated into them. These agents can work with decentralized exchanges (DEXs) and lending platforms to make trading easier, smarter and safer for users. However, some apps or bots must be downloaded to start interacting with an AI agent. For instance, an AI agent could monitor interest rate trends in Aave, optimizing lending strategies. If the interest rates for borrowing assets on Aave drop below a threshold, the AI could automatically rebalance your portfolio, shifting your assets to a more profitable lending market. In contrast, some platforms offer AI services through subscriptions. You pay a small fee, and the AI takes care of tasks like automatic trading or rebalancing your portfolio without needing you to do anything. AI agents often work through smart contracts, which are like self-executing agreements that run automatically when conditions are met. There is no need to trust an intermediary; everything is handled by code, making transactions safe and automatic. Here's how it works: Did you know? According to CoinGecko, interest in AI agents has surged, with the market cap of this niche growing by 222% to over $15 billion by the end of 2024. AI agents in decentralized finance are transforming how users manage their assets, from trading and market analysis to risk management and security. These AI-powered tools enhance DeFi platforms and help users save costs by reducing the need for professional financial firms. AI agents are taking the role of traders by automating their daily routines. While traditional bots follow pre-set rules, AI trading agents learn from market patterns and adapt their strategies in real time. They monitor price fluctuations of cryptocurrencies, identify trends and execute trades 24/7, ensuring that your portfolio is always managed with up-to-date information. They can spot arbitrage opportunities and optimize buying/selling decisions across multiple platforms. For example, an AI-powered trading agent might execute complex multi-step trades, taking advantage of price differences between various DEXs and ensuring that opportunities are not missed. Risk management in the risky DeFi world can be daunting, but AI agents can help manage it. With the ability to continuously monitor market volatility, liquidity, and borrower credit risk, AI agents provide a more accurate and real-time risk assessment than traditional systems. In DeFi lending, for example, AI agents examine a borrower's history on various platforms and offer customized collateral and loan terms based on real-time inputs. AI agents can process vast amounts of data. By scanning the price history of cryptocurrencies, social media sentiment and economic indicators, these agents are constantly learning and adapting to predict market trends. As a result, they can spot emerging trends, forecast price movements and even identify the next big DeFi project. With this information, traders and investors can stay ahead of the curve, making more informed decisions and avoiding risky markets. Security is one of the significant topics in DeFi, and AI agents can become crucial in helping detect fraudulent activities. They can analyze patterns to identify unusual behaviors, such as rapid, large withdrawals or trades that could signal a breach. Furthermore, AI agents can monitor smart contracts to detect vulnerabilities before they are exploitedexploiting them, ensuring the platform's security. As yield farming and staking pools can be highly lucrative, constant monitoring of gas fees, rewards, and interest rates for optimization is required. AI agents are adept at determining the most profitable pools to stake or farm tokens, switching strategies on the fly to compound returns. They can ensure that your assets always work for you, even when you are not actively controlling them. By acting as personalized financial assistants, AI agents can help users navigate the complexities of DeFi. They can suggest the best investment opportunities, provide portfolio advice and help users optimize their assets while saving costs -- without requiring in-depth crypto knowledge. Additionally, some agents can assist with taxes and financial research, making it easier to navigate the accounting field. This creates a more inclusive DeFi ecosystem where newcomers can participate and make informed decisions. Let's focus on creating an AI agent for portfolio management in DeFi. This AI agent will help manage and optimize your cryptocurrency holdings in a decentralized way. Did you know? In decentralized autonomous organizations (DAOs), AI agents can be leveraged to provide data-driven feedback and recommendations on governance proposals. From processing onchain information, sentiment within the community, and economic statistics, such agents help DAO participants make more informed decisions. This section explains how to create an AI agent for DeFi portfolio management that autonomously optimizes asset allocation, rebalances holdings and leverages yield farming opportunities through smart contracts. Start by defining what you want your AI agent to achieve with your crypto wallet. Common portfolio management goals include: Your AI agent will analyze your portfolio and automatically rebalance it on a regular basis every month to keep your crypto allocation within the desired percentages, adding stablecoins when volatility is high or increasing exposure to promising altcoins during a bull market. Your AI agent will need market data to make informed decisions. For portfolio management, the data includes: Use APIs like CoinGecko or CoinMarketCapto to fetch real-time price and market data. Get information on available yield opportunities from Yearn.finance or Aave. For portfolio management, a reinforcement learning model might be most appropriate. The AI will learn and adapt its actions based on rewards or penalties. This allows the agent to optimize the portfolio over time by evaluating the performance of different assets and adjusting allocations accordingly. The AI will monitor market fluctuations, adjusting asset allocation by moving funds into stablecoins during high volatility or switching into high-yield opportunities when market conditions are favorable. To implement portfolio rebalancing and other tasks autonomously, write smart contracts to handle actions like swapping assets, staking or yield farming based on the AI's recommendations. So, write a Solidity smart contract that automatically moves your holdings based on the AI's instructions. For example, if the AI detects that your portfolio has too much ETH and insufficient BTC, the smart contract will automatically swap some Ether for Bitcoin. Use a blockchain interaction library like web3.js or ethers.js to connect your AI with the DeFi protocols. This allows the AI to send transactions to DeFi platforms like Uniswap or SushiSwap to swap tokens, Aave for lending/borrowing or Compound for yield farming. The AI could determine that a particular stablecoin pool offers the best yield and instructs the smart contract to swap a portion of your crypto holdings for the stablecoin and stake it in the pool. Before deploying the AI agent, backtest it using historical data to simulate how it would have performed under various market conditions. You could run the AI agent with historical data from the past two years, simulating market crashes and rallies, to see how well it rebalances the portfolio and minimizes losses or maximizes gains. Once the AI is trained and the smart contracts are deployed, you can launch your AI-powered portfolio manager. Regularly check that the AI performs as expected and that the smart contracts execute correctly. You can set up alerts for significant changes or portfolio adjustments. For instance, you might want to monitor how often the portfolio rebalances, ensuring the AI isn't making unnecessary changes or accumulating high gas fees due to frequent swaps. You can also track the performance of your yield farming and staking efforts. While AI agents in the crypto space are gaining traction, much of the current excitement remains speculative. Researchers caution that many AI agent projects have yet to prove their utility beyond hype. One of the biggest concerns is their reliance on real-time, high-fidelity data. Errors or data manipulation can lead to unintended decisions with serious financial consequences. Mike Cahill from the Pyth Network highlights that AI agents require ultra-low-latency price updates, ideally sourced directly from first-party providers like exchanges, to reduce risks from outdated or manipulated data. While interest in AI-related crypto projects has surged, much of the AI agent niche remains speculative. Although some projects address practical challenges, the rapid development of Chinese AI models also adds competitive pressure that may lead to a sell-off among crypto AI projects, according to Sygnum Bank. Additionally, while AI enhances security, it also introduces new risks. If not properly secured, AI systems can become targets for malicious actors. Moreover, flaws in algorithms could be exploited, making security a top priority for any AI-powered DeFi platform. The regulatory environment of AI in DeFi is still nascent. Regulators and governments are concerned about algorithmic bias, data privacy and accountability. Resolving these concerns is crucial for AI to be implemented in DeFi on a large scale.